Embodiments of the present invention relate to profiling individuals, and in particular to profiling individuals based on their name.
User profiling is a well-studied problem owing to its varied applications, such as promoting goods, efficient information search, fraud detection, etc. Accordingly, various techniques for profiling users are known in the art. One profiling technique tracks the behaviors of website visitors so as to improve enterprise search and navigation results. The technique employs a knowledge index that is based on various attributes such as subject authority, work patterns, content freshness, and group know-how.
Another profiling technique enables a user to narrow their search for interesting TV programs and/or videos to watch. Given that there are a large number of TV channels, movies, etc. available for a user to watch, it is very time consuming for a user to scan through all the available channels to choose interesting ones. The technique develops a user profile either using some user specified keywords (such as action, comedy, etc.) or automatically using a history of channels watched by the user.
In another profiling technique, both static and dynamic profiles of users are used to make shopping recommendations to the users. Static profiles include such information as demographic data, purchasing preferences, etc. Dynamic profiles are captured as rules. An example rule is: “If user X travels for more than a week, then when (s)he returns, (s)he will buy a lot of groceries.”
In summary, all of the existing user profiling techniques make use of static and dynamic data of users to develop a pattern for each specific user. In other words, the information used to develop profiles is different attributes pertinent to the users. However, significant effort and resources must be used to acquire these different attributes. For example, with respect to static data such as user demographics, numerous demographics such as age, gender, income level, etc. must first be acquired from the user. With respect to dynamic data, behaviors of the user must be monitored and recorded. Accordingly, in such known systems an undesirable amount of time must be invested prior to generating a user profile in order to acquire static and/or dynamic data from the user.